Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Your profile PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust mathematical
-
areas & Group Leaders Prof. Heinz Köppl – Self-Organizing Systems Prof. Felix Hausch – Structure-based Drug Research Prof. Andreas Blaeser – Biomedical Printing Technology Prof. Torsten Frosch
-
experts can reduce the environmental impact of the chemical and agricultural industries, offer eco-friendly analytical techniques, and assess the safety of new materials. The application process in
-
testing Additional background that will be valued in the selection process: Laboratory experience Knowledge of electrochemistry and corrosion English language: Good level of English See the attached file
-
. Accordingly, we welcome all applicants who would like to commit themselves, their achievements and productivity to the success of the whole institution. At the Faculty of Physics,Institute of Applied Physics
-
welcome all applicants who would like to commit themselves, their achievements and productivity to the success of the whole institution. At the Faculty of Physics,Institute of Applied Physics, the Chair
-
: Candidates should hold a UK (or international equivalent) first or upper-second Bachelor’s degree. Candidates with backgrounds in electrical and electronic engineering, physics, computer science and
-
Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 12 days ago
about 300 people. In the Department of Living Matter Physics (LMP) we seek to fill a number of PhD positions. The LMP department engages in a wide range of theoretical research aimed at understanding
-
professors. The opportunity to make an impact for the industry and society of tomorrow. A competitive salary in a flexible working environment. For more information please contact Prof. dr. ir. Eric Demeester
-
block within this process. You will be embedded both within an experimental and computational team, providing a unique atmosphere where there is expertise to develop the deep-learning models while having